code: def env_creator(args):
      env = rps_v2.env()
      return env
  
file_path: ray/rllib/examples/rock_paper_scissors_multiagent.py
imports: import argparse
  import os
  from pettingzoo.classic import rps_v2
  import random
  import ray
  from ray import air, tune
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.algorithms.ppo import PPO, PPOConfig, PPOTF1Policy, PPOTF2Policy, PPOTorchPolicy
  from ray.rllib.env import PettingZooEnv
  from ray.rllib.examples.policy.rock_paper_scissors_dummies import BeatLastHeuristic, AlwaysSameHeuristic
  from ray.rllib.policy.policy import PolicySpec
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
  from ray.rllib.utils.test_utils import check_learning_achieved
  from ray.tune.registry import register_env
label_desc: Use image node_id 1 for calling a global function with example usage: env_creator(args) and returns: env